The Power of the Weisfeiler-Leman Algorithm for Machine Learning with Graphs

• URL: http://arxiv.org/abs/2105.05911v1
• Date: Wed, 12 May 2021 19:05:18 GMT
• Title: The Power of the Weisfeiler-Leman Algorithm for Machine Learning with Graphs
• Authors: Christopher Morris, Matthias Fey, Nils M. Kriege
• Abstract summary: We give a comprehensive overview of the Weisfeiler-Leman algorithm's use in a machine learning setting. We discuss the theoretical background, show how to use it for supervised graph- and node classification, discuss recent extensions, and its connection to neural architectures.
• Score: 13.497404066306501
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: In recent years, algorithms and neural architectures based on the Weisfeiler-Leman algorithm, a well-known heuristic for the graph isomorphism problem, emerged as a powerful tool for (supervised) machine learning with graphs and relational data. Here, we give a comprehensive overview of the algorithm's use in a machine learning setting. We discuss the theoretical background, show how to use it for supervised graph- and node classification, discuss recent extensions, and its connection to neural architectures. Moreover, we give an overview of current applications and future directions to stimulate research.

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